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Question 59

DRAG DROP

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You have an app that manages feedback.

You need to ensure that the app can detect negative comments by using the Sentiment Analysis API in Azure AI Language. The solution must ensure that the managed feedback remains on your company’s internal network.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

    Correct Answer:

Discussion
NullVoider_0

1. Provision the Language service resource in Azure. This step involves creating the Azure Language service resource, which will provide you with the necessary credentials and endpoint URL to use the Sentiment Analysis API. 2. Deploy a Docker container to an on-premises server. By deploying a Docker container on-premises, you can run the Sentiment Analysis API locally, ensuring that the feedback data does not leave your internal network. 3. Run the container and query the prediction endpoint. Once the container is running on your on-premises server, you can start sending feedback data to the Sentiment Analysis API by querying the prediction endpoint provided by the Language service.

Jimmy1017

Provision the Language service resource in Azure. Deploy a Docker container to an on-premises server. Identify the Language service endpoint URL and query the prediction endpoint.

Murtuza

Remember that the order matters: provision the language service first, then Identify the Language Service Endpoint URL and Query the Prediction Endpoint and finally deploy the container based on your chosen deployment target which is on-premises 🚀

vovap0vovap

Question stated that more ten 1 correct order possible. You can provision recourses first or deploy container first. Now Identify the Language Service Endpoint URL and Query the Prediction Endpoint should not be correct as indirectly assumed Azure Endpoint rather then local from Docker

Murtuza

Provision the Language service resource in Azure: This is the first step where you set up the Language service resource in Azure. This service will provide you with the Sentiment Analysis API. Deploy a Docker container to an on-premises server: After provisioning the Language service, you should deploy a Docker container on an on-premises server. This container will host the Azure AI Language service and ensure that the managed feedback remains on your company’s internal network. Identify the Language service endpoint URL and query the prediction endpoint: Once the Docker container is running on your on-premises server, you can identify the Language service endpoint URL. You can then query the prediction endpoint to analyze the sentiment of the comments.

Mehe323

That is correct, see prerequisites where you need to have 1) Docker installed and 2) provisioned a Language resource: https://learn.microsoft.com/en-us/azure/ai-services/language-service/sentiment-opinion-mining/how-to/use-containers

Ody__

Right, but the question says Deploy a Docker Container. It is not saying setup a Docker host. You can't run the container without having the API Key and Endpoint URI. Provision the Language service (get the API Key and Endpoint URI) Deploy a Docker container to an on-premise host Run the container and query the prediction endpoint.

Mehe323

It says 'deploy a docker container to an on-premises server', you forgot the last part. A synonym for deploy is install.

nanaw770

Deploy on-premises Provision Run

krzkrzkra

Provision the Language service resource in Azure Deploy a Docker container to an on-premises server Run the container and query the prediction endpoint